Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnly, idempotent, and non-destructive behavior. The description adds valuable context about data lag (6-12 months), keyless access, and the ability to query system-wide totals. This goes beyond what annotations provide, though it could mention rate limits or response structure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three concise sentences. The first sentence states purpose, the second gives query examples, and the third details parameters. Every sentence adds value without repetition. It is well front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, the description mentions returning 'monthly + annual recreation and total visitor counts', giving some output context. It covers input parameters comprehensively. However, it could briefly describe the return format (e.g., JSON structure) to fully compensate for the missing output schema. Given the tool's moderate complexity, this is a minor gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema coverage, baseline is 3. The description significantly adds meaning: explains park can be name or 4-letter code, notes year defaults to most recent complete year, describes optional range parameters (start_year, end_year), and clarifies system_total behavior. This helps the agent understand parameter combinations and defaults beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb (answer visitation statistics) and resource (national park visitor counts), with concrete question examples and usage examples. It clearly distinguishes from sibling tools like get_park or list_parks by focusing on visitation data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool (e.g., 'how many people visited Yellowstone') and includes example inputs. However, it does not explicitly state when not to use it or mention alternative tools for non-visitation queries, which would elevate it to a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.